Medical futility in children’s nursing: making end-of-life decisions
Bibliographic record
Abstract
Caring for infants at end of life is challenging and distressing for parents and healthcare professionals, especially in relation to making decisions regarding withholding or withdrawal of treatment. The concept of medical futility must be considered under these circumstances. Parents and healthcare professionals should be involved together in making these difficult decisions. However, for some parents, emotions and guilt often are unbearable and, understandably, parents can be reluctant to make a decision. Despite the recognition of parental autonomy, if parents disagree with a decision made by medical staff, the case will be referred to and solved by the courts. The courts' decisions are often based on the best interest of the child. In this article, the authors discuss the concepts of 'parental autonomy' and 'the child's best interests' when determining medical futility for infants or neonates. The role of the nurse when caring for the dying child and their family is multifaceted. While nurses do not have a legitimate role in decision making at the end of life, it is often nurses who, through their advocacy role, inform doctors about parents' wishes and it is often nurses who support parents during this difficult time. Furthermore, nurses caring for dying children should be familiar to the family, experienced in end-of-life care and comfortable talking to parents about death and dying and treatment choices. Children's nurses therefore require advanced communication skills and an essential understanding of the ethical and legal knowledge relating to medical futility in end-of-life children's nursing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".